Hypothesis Selection with Memory Constraints Mark Bun

Learning the probability density function of observed data is a fundamental question in statistics with numerous applications in machine learning.Variants of this problem have been studied for nearly a century. Hypothesis selection is a classic version of this problem where the goal is to learn a distribution within a pre-specified class.